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Reliability analysis on energy storage system combining GO-FLOW methodology with GERT network

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  • Li, Jingkui
  • Liu, Xiaona
  • Lu, Yuze
  • Wang, Hanzheng

Abstract

Energy storage systems are widely used in various industrial areas, playing a crucial role in improving system reliability. In the energy storage system, the batteries serve as standbys for generators and have an auxiliary regulation function, so the complex relationship between them is unable to be accurately described by the basic GO-FLOW operators. To address this issue, this paper proposes a new operator for simulating the energy storage system, employing the GERT network for modelling and calculation. In this approach, the energy storage system operator is created to represent the energy storage system with ‘n generators with l degradation states, m batteries’. Firstly, each degradation state of generators is determined. Secondly, each macro state of the energy storage system is determined by combining the states of the batteries. Finally, based on the relationships between these states, the steady-state availability of the energy storage system is obtained using the GERT algorithm. A numerical example of a repairable power supply system is employed to validate the feasibility and effectiveness of the model and algorithm. And this method holds great significance for the reliability analysis of multi-state complex systems.

Suggested Citation

  • Li, Jingkui & Liu, Xiaona & Lu, Yuze & Wang, Hanzheng, 2024. "Reliability analysis on energy storage system combining GO-FLOW methodology with GERT network," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    • Handle: RePEc:eee:reensy:v:243:y:2024:i:c:s0951832023007743
    DOI: 10.1016/j.ress.2023.109860
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    2. Li, Jingkui & Wang, Hanzheng & Tang, Yunqi & Li, Zhandong & Jiang, Xiuhong, 2025. "Reliability analysis of load-sharing system with the common-cause failure based on GO-FLOW method," Reliability Engineering and System Safety, Elsevier, vol. 254(PA).
    3. Wu, Rui & Tian, Jinpeng & Yao, Jiachi & Han, Te & Hu, Chunsheng, 2025. "Confidence-aware quantile Transformer for reliable degradation prediction of battery energy storage systems," Reliability Engineering and System Safety, Elsevier, vol. 260(C).

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